Gastric Cancer Cell Lines Have DifferentMYC-Regulated Expression Patterns but Share a Common Core of Altered Genes

Abstract

MYC is an oncogene responsible for excessive cell growth in cancer, enabling transcriptional activation of genes involved in cell cycle regulation, metabolism, and apoptosis, and is usually overexpressed in gastric cancer (GC). By using siRNA and Next-Generation Sequencing (NGS), we identified MYC-regulated differentially expressed Genes (DEGs) in three Brazilian gastric cancer cell lines representing the histological subtypes of GC (diffuse, intestinal, and metastasis). The DEGs were picked using Sailfish software, followed by Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using KEGG. We found 11 significantly enriched gene sets by using enrichment score (ES), False Discovery Rate (FDR), and nominal P-values. We identified a total of 5.471 DEGs with correlation over (80%). In diffuse-type and in metastatic GC cell lines, MYC-silencing caused DEGs downregulation, while the intestinal-type GC cells presented overall DEGs upregulation after MYC siRNA depletion. We were able to detect 11 significant gene sets when comparing our samples to the hallmark collection of gene expression, enriched mostly for the following hallmarks: proliferation, pathway, signaling, metabolic, and DNA damage response. When we analyzed our DEGs considering KEGG metabolic pathways, we found 12 common branches covering a wide range of biological functions, and three of them were common to all three cell lines: ubiquitin-mediated proteolysis, ribosomes, and system and epithelial cell signaling in Helicobacter pylori infection. The GC cell lines used in this study share 14 MYC-regulated genes, but their gene expression profile is different for each histological subtype of GC. Our results present a computational analysis of MYC-related signatures in GC, and we present evidence that GC cell lines representing distinct histological subtypes of this disease have different MYC-regulated expression profiles but share a common core of altered genes. This is an important step towards the understanding of MYC's role in gastric carcinogenesis and an indication of probable new drug targets in stomach cancer.

The m6A reader IGF2BP3 Facilitates Gastric Cancer Progression Through Activating EMT via Upregulating MYC mRNA Stability

“…By integrating results of the previous researches, the m6A2Target databases prediction, the TCGA databases, the GEO databases and the immunohistochemical (IHC) assays, we concluded that there was a positive correlation analysis of the correlation between IGF2BP3 and MYC mRNA expression levels, which indicated that IGF2BP3 may promote the progression of GC through upregulating MYC mRNA. It was reported that the MYC played a key role in cell proliferation, migration and homeostasis of GC development [26-28], and MYC was also often elevated in GC and related to poor survival and clinical late-stage [29][30][31]. What is more, through the RIP-qPCR validation method and mRNA stability experiment, we further con rmed that IGF2BP3 could promote MYC expression by direct combination with MYC mRNA to enhance the MYC mRNA stability in GC cells, consistent with the previous research [32].…”

An immune‐related seven‐lncRNA signature for head and neck squamous cell carcinoma

“…We performed GSEA of the high‐ and low‐IRLPS subgroups separated by IRLPS score with the gene sets of the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Both the false discovery rate (FDR) value <0.25 and the nominal p ‐value <0.05 were used to sort the pathways enriched in each phenotype 18,19 . Single sample GSEA (ssGSEA) analysis was then performed on several representative gene sets with the GSVA package of R, and K–M survival curves were used to explore differences in survival.…”

New prognostic markers revealed by RNA-Seq transcriptome analysis after MYC silencing in a metastatic gastric cancer cell line

“…RNA-seq was performed using Ion Proton™ platform (Thermo Fisher Scientific). Detailed methods have been described previously [43]. Crude readings were subjected to quality control check, after which the clean readings were aligned to human genome reference sequences (Hg19/GRCh37).…”

“…The methods and parameters used to identify DEGs from MYC silenced and non-silenced AGP01 cells have been previously described [43]. Results of qRT-PCR and western blot were analyzed in QuantStudio Flex Real-Time PCR Software (version 1.2.2, Thermo Fisher Scientific).…”